Moving Beyond Data Integration with Data Collaboration

Chapter 2. The Solution to the Integration Problem

The previous chapter explained why organizations struggle to share data efficiently between applications, systems, and people; why that’s a pressing problem; and what the limitations of conventional integration solutions are.

Now, let’s dive into a different approach, relying on a data collaboration platform to enable data sharing across all apps, systems, and sources without building application-specific integrations. This chapter explains what this concept means, where it came from, and how it works to solve the integration problem—or, more accurately, to help businesses move beyond it, since the ultimate value of this technique is freeing organizations from having to integrate applications at all.

We’ll discuss the data collaboration model at a high level in this chapter. Then, in the next chapter, we’ll take a look at some specific tools and vendors that enable this type of model and compare their approaches for making integration obsolete across the organization.

What Is Data Collaboration?

Put simply, data collaboration, as Figure 2-1 illustrates, is a data architecture strategy that eliminates the need for formal application-by-application integrations to allow data to flow between apps, systems, and sources and make it accessible and reusable within an organization for powering advanced analytics, operational reporting, self-serve data, and building new applications. It does this by providing data with native manageability, ...